Effect of timing of umbilical cord clamping on maternal and neonatal outcomes
Bibliographic record
Abstract
BACKGROUND: Umbilical cord clamping is one of the most commonly used medical or complementary medical interventions. The different timing of cord clamping may have any significant impact on public health. However, the results remain controversial. The aim of the study was to evaluate and compare the effect of different timing of umbilical cord clamping on maternal and neonatal outcomes. METHODS: A systematic literature search for relevant articles will be conducted in the Cochrane Central Register of Controlled Trials, PubMed, Embase, and Chinese Biomedical Literature Database from their inception to December 2018. Any randomized controlled trial (RCT), case-control study, observational study, that reported the effect of different timing of cord clamping will be included regardless of sample size. There are no language restrictions. Mortality and risk of iron-deficiency anemia will be used to assess the clinical effect. Risk of bias assessment of the included RCTs will be conducted by the Cochrane risk of bias tool and the Newcastle-Ottawa Scale is used to assess observational studies. All statistical analyses will be performed using Stata V.15.0. A modified version of Grades of Recommendation, Assessment, Development, and Evaluation will be used to assess the quality of evidence in network meta-analysis (NMA). RESULTS: The results will be published in a peer-reviewed journal. CONCLUSION: This will be the first NMA to evaluate and compare the effect of different timing of umbilical cord clamping. We hope that the results of this NMA will help clinicians and caregivers make more appropriate choices when clamping umbilical cord.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".